Amid the rapid development of generative artificial intelligence (GAI), it is essential to recognize, prevent, and mitigate the educational risks that the GAI poses to higher education. This paper begins by examining the integration of the GAI within higher education, focusing on areas such as classroom teaching, extracurricular activities, and online learning. It further investigates the closed-loop teaching process, including objectives, resources, methods, and evaluation. Additionally, the paper explores a human-centered approach that prioritizes students’ core competencies, teachers’ digital literacy, and administrators’ effective leadership. However, the GAI presents risks such as diminished academic integrity, threats to student privacy and security, challenges to the education of core societal values, reduced student innovation, strained teacher‒student relationships, and disruptions to the job market for university graduates. In response, this paper proposes strategies to address these issues: fostering a strong academic spirit, advancing AI-related legal frameworks, innovating pedagogical approaches in ideological and political courses, establishing a human-centered framework for cultivating innovation, enhancing collaboration among teachers, AI-assisted educators, and students, and reforming higher education disciplines. Collectively, these measures aim to mitigate the potential risks that the GAI introduces to higher education.

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Deep Integration of Generative Artificial Intelligence and Higher Education: Contents, Potential Risks, and Solutions

  • Xiuxi Wei,
  • Xingqiong Wei

摘要

Amid the rapid development of generative artificial intelligence (GAI), it is essential to recognize, prevent, and mitigate the educational risks that the GAI poses to higher education. This paper begins by examining the integration of the GAI within higher education, focusing on areas such as classroom teaching, extracurricular activities, and online learning. It further investigates the closed-loop teaching process, including objectives, resources, methods, and evaluation. Additionally, the paper explores a human-centered approach that prioritizes students’ core competencies, teachers’ digital literacy, and administrators’ effective leadership. However, the GAI presents risks such as diminished academic integrity, threats to student privacy and security, challenges to the education of core societal values, reduced student innovation, strained teacher‒student relationships, and disruptions to the job market for university graduates. In response, this paper proposes strategies to address these issues: fostering a strong academic spirit, advancing AI-related legal frameworks, innovating pedagogical approaches in ideological and political courses, establishing a human-centered framework for cultivating innovation, enhancing collaboration among teachers, AI-assisted educators, and students, and reforming higher education disciplines. Collectively, these measures aim to mitigate the potential risks that the GAI introduces to higher education.